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AutoEval: An Evaluation Methodology for Evaluating Query Suggestions Using Query Logs
[chapter]
2011
Lecture Notes in Computer Science
AutoEval is an evaluation methodology that assesses the quality of query modifications generated by a model using the query logs of past user interactions with the system. ...
This makes AutoEval a suitable evaluation framework for adaptive interactive search engines. ...
AutoEval is a methodology that performs simulated query recommendation experiments based on past log data to evaluate different models for generating query suggestions. ...
doi:10.1007/978-3-642-20161-5_60
fatcat:jcwee3kwirebvnso22z323qsaq
University of Essex at LogCLEF 2011: Studying Query Refinement
2011
Conference and Labs of the Evaluation Forum
We use the paradigm of ant colony optimisation to derive query suggestions and evaluate the results by applying the fully automated AutoEval methodology that relies entirely on the search logs. ...
This paper describes the analysis we performed for the query success task of LogCLEF 2011. In particular, we address the issue of query refinement. ...
AutoEval Framework We employed AutoEval which is an automatic evaluation framework for assessing the performance of query suggestion systems over time based on actual query logs.The validity of the framework ...
dblp:conf/clef/AlbakourK11
fatcat:24dprwybcbac7dpxnfmjmtnkju
Moving towards Adaptive Search in Digital Libraries
[chapter]
2011
Lecture Notes in Computer Science
We will outline how in digital libraries a domain model can automatically be acquired using search engine query logs and how it can be continuously updated using methods resembling ant colony behaviour ...
One way of helping the searcher locating the right information for a specific information need in such a collection is by providing well-structured domain knowledge to assist query modification and navigation ...
We would also like to thank Sally Chambers and The European Library as well the organisers of the LogCLEF track for providing the log files, in particular we would like to thank Thomas Mandl. ...
doi:10.1007/978-3-642-23160-5_4
fatcat:au55ukcmpvefxha3yopkjppdjq
Learning from users' querying experience on intranets
2012
Proceedings of the 21st international conference companion on World Wide Web - WWW '12 Companion
Query recommendation is becoming a common feature of web search engines especially those for Intranets where the context is more restrictive. ...
This is because of its utility for supporting users to find relevant information in less time by ...
We evaluate the effectiveness of the hybrid model using an automatic evaluation method (AutoEval) which is based on search logs data [2] by experimenting with search logs obtained over two different ...
doi:10.1145/2187980.2188197
dblp:conf/www/AdeyanjuSAKRF12
fatcat:o6zwhm5unver7lyq3n5vrmboem
Adaptation of the concept hierarchy model with search logs for query recommendation on intranets
2012
Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '12
Two adaptation approaches using query logs with and without click information are compared. ...
A concept hierarchy created from a document collection can be used for query recommendation on Intranets by ranking terms according to the strength of their links to the query within the hierarchy. ...
Evaluation methodology We use an automated evaluation framework, AutoEval, which measures the effectiveness of query recommendations over a period of time based on actual query logs [2] . ...
doi:10.1145/2348283.2348288
dblp:conf/sigir/AdeyanjuSAKRF12
fatcat:dnmtvt4n3vfbnoqs2mjhnwc67m
Dynamic User Profiling for Search Personalisation
2017
Our first chosen task is personalising search results returned by a Web search engine, and the second is the task of personalising query suggestions made by an Intranet search engine. ...
Instead of using a human-generated ontology, we use a topic modelling technique (Latent Dirichlet Allocation) for unsupervised extraction of the topics from documents. ...
Autoeval: An evaluation methodology for evaluating query suggestions using query logs. ...
doi:10.21954/ou.ro.0000c5ad
fatcat:xyzkj5owmncarfwemqnkreghee